mathematical optimization - Genetic algorithms -


I am trying to implement a genetic algorithm which will calculate the minimum and I'm having some problems.
I need to represent chromosome as a binary string and as can be explained in the list of numbers, as in the function of Rostridge there is a list of numbers in the form of a parameter?
In addition, the rostridge wants the elements present in the list-5.12 & lt; = X (i) & lt; = 5.12 What happens when I generate chromosomes then it will not generate numbers in that interval

Looking to implement a genetic algorithm, your implementation should be such that it works for any common minimum (or maximum) problem, and not only the Rastrigin function gives you a binary coded GA Or decide to implement a real coded GA . Both have their own uses and niche applications but for you, I would suggest implementing a real coded GA. According to your question, what to do if the generated variable values ​​are out of value [-5.12: 5.12], then a real coded GA and binary coded GA will handle them differently.

Always having a reference code before you start applying your own version If you are looking for a single implementation, there is a real coded GA implementation in the laboratory Is widely used by us and others. I suggest trying to play with it and try some simple optimization problems.

There is a Python Library for Genetic Algorithms and Genetic Programming.

Now, we have talked about implementing stuff, is it clear to understand your GA? If not, please see, which presents GA to the point of optimization. Please note that a binary code does not automatically translate crossover and mutation to GA for a real coded GA. Real coded GA has its own complexities, in which you will need time to read and understand some papers. There is no hurry, but with full time effort you should be able to easily go.


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